Robust estimation for semi-functional linear regression models
نویسندگان
چکیده
منابع مشابه
Robust Estimation in Linear Regression with Molticollinearity and Sparse Models
One of the factors affecting the statistical analysis of the data is the presence of outliers. The methods which are not affected by the outliers are called robust methods. Robust regression methods are robust estimation methods of regression model parameters in the presence of outliers. Besides outliers, the linear dependency of regressor variables, which is called multicollinearity...
متن کاملSemi-parametric difference-based estimation of partial linear regression models
This article describes the plreg Stata command, which implements the difference-based algorithm for estimating the partial linear regression models.
متن کاملImproved Estimation for Robust Econometric Regression Models
The t distribution has proved to be a useful alternative to the normal distribution in many econometric regression models, especially when robust estimation is desired. In this work, we consider a nonlinear heteroskedastic Student t regression model. We suppose the observations to be independently t distributed, with the location and scale parameters for each observation being related to linear...
متن کاملtruncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models
Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use. Alternative estimators, designed for the estimation of truncated regression models, have been developed. This paper presents the R package truncSP....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Statistics & Data Analysis
سال: 2020
ISSN: 0167-9473
DOI: 10.1016/j.csda.2020.107041